Residential exposure to traffic pollution and mammographic density in premenopausal women
[EN] Background Mammographic density (MD) is the most important breast cancer biomarker. Ambient pollution is a carcinogen, and its relationship with MD is unclear. This study aims to explore the association between exposure to traffic pollution and MD in premenopausal women. Methodology This Spanis...
| Autores: | , , , , , , , , , , , , , |
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| Tipo de documento: | artigo |
| Data de publicação: | 2024 |
| País: | España |
| Recursos: | Universitat Politècnica de València (UPV) |
| Repositório: | RiuNet. Repositorio Institucional de la Universitat Politécnica de Valéncia |
| Idioma: | inglês |
| OAI Identifier: | oai:riunet.upv.es:10251/207997 |
| Acesso em linha: | https://riunet.upv.es/handle/10251/207997 |
| Access Level: | Acceso aberto |
| Palavra-chave: | Traffic exposure Air pollution Breast density Premenopausal Breast cancer DDM-Madrid LENGUAJES Y SISTEMAS INFORMATICOS |
| Resumo: | [EN] Background Mammographic density (MD) is the most important breast cancer biomarker. Ambient pollution is a carcinogen, and its relationship with MD is unclear. This study aims to explore the association between exposure to traffic pollution and MD in premenopausal women. Methodology This Spanish cross-sectional study involved 769 women attending gynecological examinations in Madrid. Annual Average Daily Traffic (AADT), extracted from 1944 measurement road points provided by the City Council of Madrid, was weighted by distances (d) between road points and women's addresses to develop a Weighted Traffic Exposure Index (WTEI). Three methods were employed: method-1 (1dAADT), method-2 (1dAADT), and method-3 (e1dAADT). Multiple linear regression models, considering both log-transformed percentage of MD and untransformed MD, were used to estimate MD differences by WTEI quartiles, through two strategies: "exposed (exposure buffers between 50 and 200 m) vs. not exposed (>200 m)"; and "degree of traffic exposure". Results Results showed no association between MD and traffic pollution according to buffers of exposure to the WTEI (first strategy) for the three methods. The highest reductions in MD, although not statistically significant, were detected in the quartile with the highest traffic exposure. For instance, method-3 revealed a suggestive inverse trend (e(Q1)(beta) = 1.23, e(Q2)(beta) = 0.96, e(Q3)(beta) = 0.85, e(Q4)(beta) = 0.85, p-trend = 0.099) in the case of 75 m buffer. Similar non-statistically significant trends were observed with Methods-1 and -2. When we examined the effect of traffic exposure considering all the 1944 measurement road points in every participant (second strategy), results showed no association for any of the three methods. A slightly decreased MD, although not significant, was observed only in the quartile with the highest traffic exposure: e(Q4)(beta) = 0.98 (method-1), and e(Q4)(beta) = 0.95 (methods-2 and -3). Conclusions Our results showed no association between exposure to traffic pollution and MD in premenopausal women. Further research is needed to validate these findings. |
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